Comparative Analysis Between Olink-PEA and Alamar-NULISA Proteomic Technologies Applied to a Critically Ill COVID-19 Cohort.

IF 3.4 4区 生物学 Q2 BIOCHEMICAL RESEARCH METHODS Proteomics Pub Date : 2025-02-10 DOI:10.1002/pmic.202400456
Sara Taleb, Nisha Stephan, Sareena Chennakkandathil, Muhammad Umar Sohail, Sondos Yousef, Hina Sarwath, Muna Al-Noubi, Karsten Suhre, Ali Ait Hssain, Frank Schmidt
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引用次数: 0

Abstract

We aim to verify and validate low-abundant plasma proteins from severe COVID-19 cases and controls through a comparative analysis between Olink and Alamar performances. Eighty-three severe cases and 44 controls were measured for proteomics using three Olink panels and one Alamar panel, which share 94 targets. CV, pairwise correlation of intensity signals, and detectability range were compared across platforms. Statistical comparisons were performed using FDR-adjusted linear models with age as a covariate to construct differential protein abundance volcano plots between cases and controls per platform and heatmaps between our cohort and five public cohorts. Overall, pairwise comparisons (n = 94) showed strong correlations among cases (r = 0.82) and controls (r = 0.7). 60/94 proteins had mutual significance on both platforms; of which 54 showed concordant effect direction, and six showed opposite effect direction (IL-6R, IL-1R2, KITLG, TSLP, IL-17C, and IL-4R). Alamar verified 80 and 60 targets from cases and controls, respectively, along with 54 differential proteins from Olink. Compared to public cohorts measured by Olink, our Olink data showed consistent findings from 28 proteins, of which 27 were validated by Alamar.

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来源期刊
Proteomics
Proteomics 生物-生化研究方法
CiteScore
6.30
自引率
5.90%
发文量
193
审稿时长
3 months
期刊介绍: PROTEOMICS is the premier international source for information on all aspects of applications and technologies, including software, in proteomics and other "omics". The journal includes but is not limited to proteomics, genomics, transcriptomics, metabolomics and lipidomics, and systems biology approaches. Papers describing novel applications of proteomics and integration of multi-omics data and approaches are especially welcome.
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